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Precision Health Database


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Reproductive and Child Health

Last data update: Oct 19, 2021. (Total: 42878 Documents since 2012)
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Machine learning algorithms for predicting undernutrition among under-five children in Ethiopia.
Bitew Fikrewold H et al. Public health nutrition 2021 1-29
Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse.
Kummervold Per E et al. JMIR medical informatics 2021 9(10) e29584
Comparison of machine learning algorithms applied to symptoms to determine infectious causes of death in children: national survey of 18,000 verbal autopsies in the Million Death Study in India.
Idicula-Thomas Susan et al. BMC public health 2021 21(1) 1787
A new approach to a legacy concern: Evaluating machine-learned Bayesian networks to predict childhood lead exposure risk from community water systems.
Mulhern Riley et al. Environmental research 2021 204(Pt B) 112146
The TVGH-NYCU Thal-Classifier: Development of a Machine-Learning Classifier for Differentiating Thalassemia and Non-Thalassemia Patients.
Fu Yi-Kai et al. Diagnostics (Basel, Switzerland) 2021 11(9)
Provider Perspectives on the Acceptability, Appropriateness, and Feasibility of Teleneonatology.
Fang Jennifer L et al. American journal of perinatology 2021
Novel Application of Machine Learning Algorithms and Model-Agnostic Methods to Identify Factors Influencing Childhood Blood Lead Levels.
Liu Xiaochi et al. Environmental science & technology 2021
Evaluation of artificial intelligence using time-lapse images of IVF embryos to predict live birth.
Sawada Yuki et al. Reproductive biomedicine online 2021
Combining Resampling Strategies and Ensemble Machine Learning Methods to Enhance Prediction of Neonates with a Low Apgar Score After Induction of Labor in Northern Tanzania.
Tarimo Clifford Silver et al. Risk management and healthcare policy 2021 143711-3720
Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review.
Chen Zhiyi et al. Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine 2021
Assess A Smartphone App (AICaries) that uses artificial intelligence to detect dental caries in children and provide interactive oral health education: Protocol for design and usability testing.
Xiao Jin et al. JMIR research protocols 2021
Perinatal health predictors using artificial intelligence: A review.
Ramakrishnan Rema et al. Women's health (London, England) 2021 1717455065211046132
Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.
Sazawal Sunil et al. BMC pregnancy and childbirth 2021 21(1) 609
Understanding Pediatric Surgery Cancellation: Geospatial Analysis.
Liu Lei et al. Journal of medical Internet research 2021 23(9) e26231
Glomerular Disease Classification and Lesion Identification by Machine Learning.
Yang Cheng-Kun et al. Biomedical journal 2021
[Electroencephalogram feature extraction and classification of autistic children based on recurrence quantification analysis].
Zhao Jie et al. Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi 2021 38(4) 663-670
Classification of Children With Autism and Typical Development Using Eye-Tracking Data From Face-to-Face Conversations: Machine Learning Model Development and Performance Evaluation.
Zhao Zhong et al. Journal of medical Internet research 2021 23(8) e29328
Artificial intelligence manages congenital cataract with individualized prediction and telehealth computing.
Long Erping et al. NPJ digital medicine 2021 3(1) 112
Machine learning with neuroimaging data to identify autism spectrum disorder: a systematic review and meta-analysis.
Song Da-Yea et al. Neuroradiology 2021
Machine learning powered tools for automated analysis of muscle sympathetic nerve activity recordings.
Nolde Janis M et al. Physiological reports 2021 9(16) e14996
Use of Data to Understand the Social Determinants of Depression in Two Middle-Income Countries: the 3-D Commission.
Thapa Bishnu et al. Journal of urban health : bulletin of the New York Academy of Medicine 2021
Pediatric sepsis screening in US hospitals.
Eisenberg Matthew A et al. Pediatric research 2021
LightGBM: an efficient and accurate method for predicting pregnancy diseases.
Liao Hualong et al. Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology 2021 1-10
Application of Artificial Intelligence to Cardiovascular Computed Tomography.
Yang Dong Hyun et al. Korean journal of radiology 2021
Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care.
Dong Junzi et al. Critical care (London, England) 2021 25(1) 288
Machine Learning-Enabled Determination of Diffuseness of Brain Arteriovenous Malformations from Magnetic Resonance Angiography.
Jiao Yuming et al. Translational stroke research 2021
Ethics of Artificial Intelligence in Medicine and Ophthalmology.
Abdullah Yasser Ibraheem et al. Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) 2021 10(3) 289-298
Evaluation of artificial intelligence-based quantitative analysis to identify clinically significant severe retinopathy of prematurity.
Li Jie et al. Retina (Philadelphia, Pa.) 2021
Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.
Duran Ibrahim et al. Developmental medicine and child neurology 2021
Identifying Risk Factors for Complicated Post-operative Course in Tetralogy of Fallot Using a Machine Learning Approach.
Faerber Jennifer A et al. Frontiers in cardiovascular medicine 2021 8685855
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